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Motion capture data recovery using skeleton constrained singular value thresholding

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Abstract

Motion capture data could be missing due to imperfections during the acquisition process. Singular value thresholding (SVT) is an effective method to recover missing motion capture data. However, its effectiveness decreases significantly when markers are missing for longer periods of time. To alleviate this problem, we utilize the fact that human bones are rigid to constrain inter-marker distances of specific sets of markers. We extend the SVT method for mocap recovery to include skeleton constraints. On average, our proposed method improves on the SVT method by 40 %, and performs 4 % better than a recent state-of-the-art method at up to 11 times faster computation time.

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Notes

  1. Mocap data values are scaled down for algorithm stability as recommended, but are not transformed to local coordinates. All parameters are left at default values.

  2. All mocap data values in this paper are expressed in units from the CMU mocap database. To obtain values in millimetres, multiply them by 56.44.

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Authors and Affiliations

  1. School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, Singapore

    Cheen-Hau Tan, JunHui Hou & Lap-Pui Chau

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  1. Cheen-Hau Tan
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  2. JunHui Hou
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Correspondence to Lap-Pui Chau.

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Tan, CH., Hou, J. & Chau, LP. Motion capture data recovery using skeleton constrained singular value thresholding. Vis Comput 31, 1521–1532 (2015). https://doi.org/10.1007/s00371-014-1031-5

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